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Ma, L. (author), Qiu, Z. (author), Van Mieghem, P.F.A. (author), Kitsak, M.A. (author)
Epidemic forecasts are only as good as the accuracy of epidemic measurements. Is epidemic data, particularly COVID-19 epidemic data, clean, and devoid of noise? The complexity and variability inherent in data collection and reporting suggest otherwise. While we cannot evaluate the integrity of the COVID-19 epidemic data in a holistic fashion, we...
journal article 2024
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Achterberg, M.A. (author), Prasse, B. (author), Ma, L. (author), Trajanovski, S. (author), Kitsak, M.A. (author), Van Mieghem, P.F.A. (author)
Researchers from various scientific disciplines have attempted to forecast the spread of coronavirus disease 2019 (COVID-19). The proposed epidemic prediction methods range from basic curve fitting methods and traffic interaction models to machine-learning approaches. If we combine all these approaches, we obtain the Network Inference-based...
journal article 2022
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Ma, L. (author), Kitsak, M.A. (author), Van Mieghem, P.F.A. (author)
Despite many studies on the transmission mechanism of the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), it remains still challenging to efficiently reduce mortality. In this work, we apply a two-population Susceptible-Infected-Removed (SIR) model to investigate the COVID-19 spreading when contacts between elderly and non...
conference paper 2022